Flexible eyewear device with dual cameras for generating stereoscopic images

ABSTRACT

Three-dimensional image calibration and presentation for eyewear including a pair of image capture devices is described. Calibration and presentation includes obtaining a calibration offset to accommodate flexure in the support structure for the eyewear, adjusting a three-dimensional rendering offset by the obtained calibration offset, and presenting the stereoscopic images using the three-dimension rendering offset.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of U.S. application Ser. No.17/521,001 filed on Nov. 8, 2021, which is a Continuation of U.S.application Ser. No. 16/688,046 filed on Nov. 19, 2019, now U.S. Pat.No. 11,212,509, which claims priority to U.S. Provisional ApplicationSer. No. 62/782,885 filed on Dec. 20, 2018, the contents of all of whichare incorporated fully herein by reference.

TECHNICAL FIELD

The present subject matter relates to image capture eyewear, e.g., smartglasses, and, more particularly, to image capture eyewear with dualcameras for generating stereoscopic images.

BACKGROUND

Stereoscopic images of a scene are useful to create a three-dimensionaleffect. Typically, a first camera captures a first image of the scene,and a second camera captures a second image of the same scene. The firstand second cameras have a fixed relationship to one another. Athree-dimensional display system presents the captured first image to aneye of an observer and the captured second image to the other eye of theobserver to create the desired three-dimensional effect. Therelationship between the first and second cameras is important in orderto provide a realistic three-dimensional effect. If the relationshipbetween the first and second cameras deviates from the fixedrelationship, e.g., due to bending of the support structure on which thecameras are mounted, the three-dimensional experience is adverselyaffected.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings depict implementations, by way of example only, not by wayof limitations. In the figures, like reference numerals refer to thesame or similar elements. When a plurality of similar elements ispresent, a single reference numeral may be assigned to the plurality ofsimilar elements with a small letter designation referring to specificelements. When referring to the elements collectively or to anon-specific one or more of the elements, the small letter designationmay be dropped.

FIG. 1A is a perspective view of an image capture eyewear exampleincluding dual cameras and a support structure supporting the dualcameras and other electronic components.

FIG. 1B is a top view of the image capture eyewear example of FIG. 1Aillustrating a region defined by the image capture eyewear for receivinga head of a user wearing the image capture eyewear.

FIG. 1C is a top-side view of the image capture eyewear example of FIG.1A showing the locations of the dual cameras and the flexibility of theeyewear.

FIG. 1D is another top-side view of the image capture eyewear example ofFIG. 1A showing the respective fields of view of the dual cameras atdifferent flex positions.

FIG. 2 is a block diagram of an example of the electronic componentssupported by the image capture eyewear example of FIG. 1A, andcommunication with a personal computing device and a recipient through anetwork.

FIG. 3A is a flowchart showing an example of the operation of the dualcamera eyewear for performing calibration of the dual cameras; and

FIG. 3B is a flowchart showing further details of the example of theoperation of the dual camera eyewear for performing stereoscopic imagingusing the calibration results.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth by way of examples in order to provide a thorough understanding ofthe relevant teachings. However, it should be apparent to those skilledin the art that such details are not necessary to practice the presentteachings. In other instances, a relatively high-level description,without detail, of well-known methods, procedures, components, andcircuitry avoids unnecessarily obscuring aspects of the presentteachings.

The term “coupled” as used herein refers to any logical, optical,physical, or electrical connection, link or the like by which signals orlight produced or supplied by one system element are imparted to anothercoupled element. Unless described otherwise, coupled elements or devicesare not necessarily physically connected to one another and may beseparated by airspace, intermediate components, elements, orcommunication media that may modify, manipulate, or carry the light orsignals.

The orientations of the image capture eyewear, associated components,and any devices incorporating an LED such as shown in any of thedrawings, are by way of example only, for illustration and discussionpurposes. In operation, orientation of the image capture eyewear may bein other directions suitable to the particular application of the imagecapture eyewear, for example up, down, sideways, or any otherorientation. Also, any directional term, such as front, rear, inwards,outwards, towards, left, right, lateral, longitudinal, up, down, upper,lower, top, bottom and side, is exemplary, and not limiting, as todirection or orientation.

Example image capture eyewear has an optical element, electroniccomponents, a support structure configured to support the opticalelement and the electronic components including dual cameras, and adisplay system coupled to the electronic components and supported by thesupport structure. The dual cameras capture stereoscopic images for usein rendering three dimensional images and/or creating athree-dimensional effect.

FIG. 1A depicts a front perspective view of a first camera 10 and asecond camera 11 on example image capture eyewear 12. The illustratedimage capture eyewear 12 includes a support structure 13 that hastemples 14A and 14B extending from a central frame portion 16. Imagecapture eyewear 12 additionally includes articulated joints 18A and 18B,electronic components 20A and 20B, and core wires 22A, 22B and 24.Although the illustrated image capture eyewear 12 are glasses, the imagecapture eyewear may take other forms such as a headset, head gear,helmet, or other device that may be worn by the user.

Support structure 13 supports the first and second cameras 10, 11.Support structure 13 also supports one or more optical elements within afield of view of a user when worn by the user. For example, centralframe portion 16 supports the one or more optical elements. As usedherein, the term “optical elements” refers to lenses, transparent piecesof glass or plastic, projectors, screens, displays and other devices forpresenting visual images or through which a user perceives visualimages. In an example, respective temples 14A and 14B connect to centralframe portion 16 at respective articulated joints 18A and 18B. Theillustrated temples 14A and 14B are elongate members having core wires22A and 22B extending longitudinally therein.

Temple 14A is illustrated in a wearable condition and temple 14B isillustrated in a collapsed condition in FIG. 1A. As shown in FIG. 1A,articulated joint 18A connects temple 14A to a right end portion 26A ofcentral frame portion 16. Similarly, articulated joint 18B connectstemple 14B to a left end portion 26B of central frame portion 16. Theright end portion 26A of central frame portion 16 includes a housingthat carries electronic components 20A therein. The left end portion 26Balso includes a housing that carries electronic components 20B therein.The housings may be integrally formed with the central frame, integrallyformed with the respective temples 14A, 14B, or formed as separatecomponents.

A plastics material or other material embeds core wire 22A, whichextends longitudinally from adjacent articulated joint 18A toward asecond longitudinal end of temple 14A. Similarly, the plastics materialor other material also embeds core wire 22B, which extendslongitudinally from adjacent articulated joint 18B toward a secondlongitudinal end of temple 14B. The plastics material or other materialadditionally embeds core wire 24, which extends from the right endportion 26A (terminating adjacent electronic components 20A) to left endportion 26B (terminating adjacent electronic components 20B).

Electronic components 20A and 20B are carried by support structure 13(e.g., by either or both of temple(s) 14A, 14B and/or central frameportion 16). Electronic components 20A and 20B include a power source,power and communication related circuitry, communication devices,display devices, a computer, a memory, modules, and/or the like (notshown). Electronic components 20A and 20B may also include or supportdual cameras 10 and 11 for capturing images and/or videos from differentperspectives. These images may be fused to generate a stereoscopicimages/videos. Also included, but not shown in the figure, are indicatorLEDs indicating the operational state of image capture eyewear and oneor more microphones for capturing audio that coincides with the capturedvideo.

In one example, temples 14A and 14B and central frame portion 16 areconstructed of a plastics material, cellulosic plastic (e.g., cellulosicacetate), an eco-plastic material, a thermoplastic material, or thelike, with core wires 22A, 22B and 24 embedded therein. Core wires 22A,22B and 24 provide structural integrity to support structure 13 (i.e.,temple(s) 14A, 14B and/or central frame portion 16). Additionally, corewires 22A, 22B and/or 24 act as a heat sink to transfer heat generatedby electronic components 20A and 20B away therefrom so as to reduce thelikelihood of localized heating adjacent electronic components 20A and20B. As such, core wires 22A, 22B and/or 24 thermally couple to the heatsource to provide a heat sink for the heat source. Core wires 22A, 22Band/or 24 may include relatively flexible conductive metal or metalalloy material such as one or more of an aluminum, an alloy of aluminum,alloys of nickel-silver, and a stainless steel, for example.

As illustrated in FIG. 1B, support structure 13 defines a region (e.g.,region 52 defined by the frame 12 and temples 14A and 14B) for receivinga portion 52 (e.g., the main portion) of the head of the user/wearer.The defined region(s) are one or more regions containing at least aportion of the head of a user that are encompassed by, surrounded by,adjacent, and/or near the support structure when the user is wearing theimage capture eyewear 12.

As described above, image capture eyewear 12 has dual cameras 10, 11 forcapturing stereoscopic images. A simplified overhead view of the dualcameras 10, 11 is shown in FIG. 1C, where frame 13 includes cameras 10,11 integrated into respective, opposite sides (i.e., left and rightsides) of frame 13. The first camera 10 has a first sight line 30 andthe second camera 11 has a second sight line 31. In an example, absentflexing of the frame 13, the first and second sight lines 30, 31 aresubstantially parallel. Generally, stereoscopic imaging is a techniquefor generating what appears to be a three-dimensional (3D) image havingdepth from two or more offset two-dimensional (2D) images. Stereoscopicimaging is performed naturally by humans who capture offset images withtheir respective left and right eyes. These offset images are thencombined by the brain to form what appears to be a 3D image (i.e., animage with depth).

Generation of three-dimensional images and/or creation of athree-dimensional effect generally requires the fusion of stereoscopicimages. For example, a stereoscopic imaging algorithm may create athree-dimensional image by fusing the stereoscopic images using theknown sight lines, separation of the sight lines, and/or fields of viewof the cameras. A stereoscopic imaging algorithm may create athree-dimensional effect by presenting a first of the stereoscopicimages to a first eye of an observer via a display and a second of thestereoscopic images to a second eye of the observer via the same or adifferent display using the known sight lines, separation of the sightlines, and/or fields of view of the cameras.

The stereoscopic imaging algorithm can extract depth information bycomparing information about a scene from the stereoscopic images, e.g.,by examining the relative positions of objects in the two images. Intraditional stereo vision, two cameras, displaced horizontally from oneanother are used to obtain two differing views on a scene. By comparingthese two images, the relative depth information can be obtained in theform of a disparity map, which encodes the difference in horizontalcoordinates of corresponding image points. The values in this disparitymap are inversely proportional to the scene depth at the correspondingpixel location.

For a human to experience a three-dimensional effect, a stereoscopicdevice may superimpose the stereoscopic images, with the image from theright camera 10 being shown to the observer's right eye and from theleft camera 11 being shown to the left eye. The images may bepre-processed to increase picture quality. For example, the images mayfirst be processed to remove distortion (e.g., due to having beenacquired with a “fisheye” lens). For example, barrel distortion andtangential distortion may be removed to ensure the observed imagematches the projection of an ideal pinhole camera. The image mayadditionally be projected back to a common plane to allow comparison ofthe image pairs, known as image rectification. An information measurewhich compares the two images is minimized. This gives the best estimateof the position of features in the two images and creates a disparitymap. Optionally, the received disparity map is projected into athree-dimensional point cloud. By utilizing the cameras' projectiveparameters, the point cloud can be computed such that it providesmeasurements at a known scale.

The algorithm(s) for presenting the stereoscopic images to produce athree-dimensional effect is dependent on the relative sightlines/fieldsof views between the respective cameras. Without this information, thealgorithm(s) may not be able to properly fuse/display the stereoscopicimages to achieve the desired three-dimensional effect.

All eyewear has a stiffness that enables support of the eyewearcomponents, while allowing for some flexibility for user comfort. Thisflexibility, however, complicates the capture of suitable stereoscopicimages to produce a desired three-dimensional effect, which, asdescribed above, require the cameras to have a known sight lines/fieldsof view with respect to one another.

For example, the stereoscopic imaging algorithm may be set based on theknown fields of view of the cameras as shown FIG. 1C, which have sightlines that are substantially parallel to each other. As illustrated inFIG. 1D, however, when the user places eyewear 12 on their head, frame13 may flex due to temples 14A, 14B bowing outward to bowed templepositions 14A′, 14B′, resulting in a change in the orientation of thecameras 10, 11. When the orientation of the cameras 10, 11 change, theoriginal sight lines 30, 31 of cameras 10, 11 shift by a respectivevariable angle 23A, 23B to flexed sight lines 30′, 31′ for new cameraorientation 10′, 11′. Thus, the sight lines 30′ 31′ of cameras 10 and 11would no longer be parallel to each other.

The variable angles 23A, 23B resulting from this flexing are dependenton the stiffness of the temples 14A, 14B, the stiffness of the frame 13,the size of the user's head, etc. Thus, the relative fields of view ofcameras 10 and 11 may be different for different wearers. The unflexedfield of view of camera 10 changes by angle 23A from a field of viewrepresented by lines 25A to 25B to a field of view represented by 25A′to 25B′. The unflexed field of view of camera 11 changes by angle 23Bfrom a field of view represented by lines 25C to 25D to a field of viewrepresented by 25C′ to 25D′. In an example, a stereoscopic imagealgorithm calibrates the cameras to determine their relative fields ofview.

Only two flexure states are illustrated in FIG. 1D, however, flexure mayoccur along and/or around essentially any axis extending through theeyewear 12. The range of flexure may have a minimum and a maximum thatis dependent on the structural stiffness of frames 13. In general, asthe frame stiffness increases and/or the temple stiffness decreases, therange of flexure decreases. Therefore, the eyewear may be designed andmanufactured with a predetermined stiffness that limits the flexurerange to an acceptable level along all axis and angles of flexure. Thestiffness may be designed based on the materials used to construct theframe. For example, a crossbar (e.g., metal) may be integrated in theframes along line 21 to limit the flexure of the frames and thus limitthe movement of the sight lines/fields of view of cameras 10, 11 to apredetermined range acceptable for producing the stereoscopic image.

Generally, the eyewear 12 performs a calibration prior to generatingstereoscopic images. The calibration algorithm includes capturing imagesfrom both cameras 10 and 11 and determining the relative fields of viewbetween the cameras by matching features between corresponding imagescaptured by each of the cameras (i.e., what is the relative movement ofa feature between right camera 10 and left camera 11. This calibrationmay be performed automatically by the eyewear, or upon user request(e.g., the user pressing a button such as button 32 (FIG. 1B)). Oncecalibration is performed, the eyewear may capture stereoscopic imagesfor use in producing three dimensional images and/or producing threedimensional effects by taking into account changes to the sightlines/fields of view.

FIG. 2 is a block diagram of example electronic components of eyewearcapable of performing calibration and rending/displaying threedimensional images taking into account changes in sight lines/fields ofview as described above. The illustrated electronic components include acontroller 100 (e.g., lower power processor, image processor, etc.) forcontrolling the various devices in the image capture eyewear 12; awireless module (e.g., Bluetooth™) 102 for facilitating communicationbetween the image capture eyewear 12 and a client device (e.g., apersonal computing device 50); a power circuit 104 (e.g., battery,filter, etc.) for powering image capture eyewear 12; a flash storage 106for storing data (e.g., images, video, image processingalgorithms/software, etc.); a distance measuring device 108 such as alaser measuring device; a selector 32; and dual cameras 10, 11 forcapturing the images and/or a series of images (e.g., video), and amicrophone (not shown) for capturing sound. Although the image captureeyewear 12 and the personal computing device 50 are illustrated asseparate components, the functionality of the personal computing device50 may be incorporated into the image capture eyewear 12 enabling theimage capture eyewear 12 to directly send a stereoscopic image(s) to oneor more recipients (e.g., recipients 51 via Internet 53) without theneed for a separate computing device. Additionally, processing describedherein as performed by eyewear 12 (e.g., one or more steps of thecalibration and stereoscopic algorithms) may be performed by a remoteprocessor coupled to the eyewear device 12 such as a processor withinthe personal computing device 50.

The selector 32 may trigger (e.g., responsive to a momentary push of abutton) controller 100 of image capture eyewear 12 to captureimages/video for a calibration algorithm and/or stereoscopic imagingalgorithm. In an example, the selector 32 may be a physical button onthe eyewear 12 that, when pressed, sends a user input signal to thecontroller 100. The controller 100 may interpret pressing the button fora predetermined period of time (e.g., three seconds) as a request toperform the calibration algorithm and/or the stereoscopic imagingalgorithm. In other examples, the selector 32 may be a virtual button onthe eyewear or another device. In yet another example, the selector maybe a voice module that interprets voice commands or an eye detectionmodule that detects where the focus of an eye is directed. Controller100 may also interpret signals from selector 32 as a trigger to selectan intended recipient of the image(s) (e.g., user paired smartphone 50,or remote smartphone 51 via network 53).

Wireless module 102 may couple with a client/personal computing device50 such as a smartphone, tablet, phablet, laptop computer, desktopcomputer, networked appliance, access point device, or any other suchdevice capable of connecting with wireless module 102. Bluetooth,Bluetooth LE, Wi-Fi, Wi-Fi direct, a cellular modem, and a near fieldcommunication system, as well as multiple instances of any of thesesystems, for example, may implement these connections to enablecommunication there between. For example, communication between thedevices may facilitate transfer of software updates, images, videos,lighting schemes, and/or sound between image capture eyewear 12 and theclient device.

In addition, personal computing device 50 may be in communication withone or more recipients (e.g., recipient personal computing device 51)via a network 53. The network 53 may be a cellular network, Wi-Fi, theInternet or the like that allows personal computing devices to transmitand receive an image(s), e.g., via text, email, instant messaging, etc.

Cameras 10, 11 for capturing the images/video may include digital cameraelements such as a charge-coupled device, a lens, or any other lightcapturing elements for capturing image data for conversion into anelectrical signal(s). Cameras 10, 11 may additionally or alternativelyinclude a microphone having a transducer for converting sound into anelectrical signal(s).

The controller 100 controls the electronic components. For example,controller 100 includes circuitry to receive signals from cameras 10, 11and process those signals into a format suitable for storage in memory106 (e.g., flash storage). Controller 100 powers on and boots to operatein a normal operational mode, or to enter a sleep mode. In one example,controller 100 includes a microprocessor integrated circuit (IC)customized for processing sensor data from camera 10, along withvolatile memory used by the microprocessor to operate. The memory maystore software code for execution by controller 100 (e.g., execution ofthe calibration algorithm, the stereoscopic imaging algorithm, recipientselection, transmission of images, etc.).

Each of the electronic components require power to operate. Powercircuit 104 may include a battery, power converter, and distributioncircuitry (not shown). The battery may be a rechargeable battery such aslithium-ion or the like. Power converter and distribution circuitry mayinclude electrical components for filtering and/or converting voltagesfor powering the various electronic components.

Calibration Algorithm

FIG. 3A depicts a calibration process 300. As described above, prior toperforming stereoscopic imaging, the eyewear performs a calibrationprocess to determine the relative difference between current lines ofsight/fields of views of the stereoscopic cameras (e.g., cameras 11) tostandard sight lines/fields of view for eyewear not experiencing anyflexure. This is beneficial to ensuring that the stereoscopic imagingalgorithm is able to correctly combine the images to produce a qualitystereoscopic image.

At block 302, the eyewear captures stereoscopic images of a scenecontaining at least one object with known dimensions (referred to hereinas a known scene). Eyewear 12 may capture a right raw image of the knownscene with right camera 10 and a left raw image of the known scene withleft camera 11. In an example, the known scene has sharp features thatare easily detectable by an image processing algorithm such as ScaleInvariant Feature Transforms (SIFT) or Binary Robust Invariant ScalableKeypoints (BRISK). In another example, a trained deep neural network(DNN) can identify known objects such as people or cars.

At block 303, the images obtained at block 303 are rectified to removedistortion. Controller 100 may rectify the images to remove distortionintroduced by the respective lenses of the cameras (e.g., distortion atthe edges of the lens resulting from vignetting) to facilitatecomparison of features between images. The right raw image is rectifiedto create a right rectified image and the left raw image is rectified tocreate the right rectified image.

At block 304, the calibration algorithm obtains a distance to a knownfeature in the known scene. In one example, the calibration algorithmrun by controller 100 determines the distance to the known feature basedon the size of the known feature in the captured image(s), e.g., thenumber of pixels covered by the known feature in a horizontal and/orvertical direction. In another example, the height/width of detectedknown objects are determined from bounding rectangles detected by a DNN.A DNN may also be trained to directly estimate a distance to a knownobject. In another example, the calibration algorithm receives thedistance from a distance measuring device 108 such as a laser measuringdevice incorporated into the eyewear.

At block 306, the calibration algorithm identifies an actual offsetbetween the stereoscopic images for one or more features in the knownscene. The calibration algorithm may compare an offset for a knownfeature(s) in one image (e.g., a left raw or rectified image to thatknow feature(s) in another image (e.g., a right raw or rectified image).In an example, the number of pixels between the position of the featurein the left image and the position of the feature in the right image(e.g., in a horizontal direction) is the actual offset.

At block 308, the calibration algorithm determines a calibration offset.In an example, the calibration offset is a difference between the actualoffset and a previously determined offset for the one or more featuresin the known scene determined with eyewear not experiencing any flexure.

In an alternative embodiment, the calibration offset is determined basedon an amount of flexure experienced by the eyewear. The amount offlexure may be estimated based on a value generated by a strain gauge inthe frame of the eyewear. For example, predefined offset values may beassociated with predefined levels of strain (e.g., none, low, medium,and high). A difference calibration offset may be determined for eachflexure amount (e.g., using steps 302 308) enabling the system toproperly render and display stereoscopic images taking into account theamount of flexure.

At block 310, store the calibration offset(s). In an example, thecalibration algorithm stores the calibration offset(s) in memory 106accessible by controller 100, e.g., for use in generating stereoscopicimages. The controller 100 may store each calibration offset along witha flexure amount corresponding to the offset.

Stereoscopic Algorithm

FIG. 3B depicts a three-dimensional presentation process 320. Asdescribed above, after the calibration is complete, the eyewear mayperform stereoscopic imaging to render/display three dimensional images.

At block 322, the eyewear obtains stereoscopic images of a scene.Eyewear 12 may capture a right raw image of the known scene with rightcamera 10 and a left raw image of the known scene with left camera 11.

At block 324, the stereoscopic algorithm rectifies the obtained rawstereoscopic images to correct distortion in the stereoscopic images.Controller 100 may rectify the images to remove distortion introduced bythe respective lenses of the cameras (e.g., distortion at the edges ofthe lens resulting from vignetting) to facilitate comparison of featuresbetween images. The right raw image is rectified to create a rightrectified image and the left raw image is rectified to create the rightrectified image.

At block 326, the stereoscopic algorithm obtains a calibration offset(e.g., from the process described above with respect to FIG. 3A). In anexample, controller 100 retrieves the calibration offset from memory106. Controller 100 may first determine an amount of flexure the frame12 is experiencing and select a calibration offset from memory 106corresponding to the amount of flexure.

At block 328, the stereoscopic algorithm adjusts a three-dimensionalrendering offset (i.e., an offset between two captured images of a scenecaptured by cameras having a known relationship to one another in orderto provide a three-dimensional effect) in a rendering algorithm by theobtained calibration offset. In an example, controller 100 adjusts thethree-dimensional rendering offset by the calibration offset.

At block 330, the stereoscopic algorithm presents three dimensionalimages based on the rendered stereoscopic images using the adjustedoffset. In an example, the stereoscopic algorithm presents the right andleft images of the stereoscopic images to the right and left eyes,respectively, of an observer (e.g., via displays of the eyewear). Thepresented images are projected, taking the adjusted offset into account,in order provide a more realistic three-dimensional effect to thewearer. In another example, the stereoscopic algorithm blends the rightand left images of the stereoscopic images on a display, taking theadjusted offset into account, in order provide a more realisticthree-dimensional effect to the viewer.

The steps in FIGS. 3A and 3B may be performed by controller 100 of theelectronic components and/or the personal computing device upon loadingand executing software code or instructions which are tangibly stored ona tangible computer readable medium, such as on a magnetic medium, e.g.,a computer hard drive, an optical medium, e.g., an optical disc,solid-state memory, e.g., flash memory, or other storage media known inthe art. Thus, any of the functionality performed by the controller 100or personal computing device 50 described herein, such as the steps inFIGS. 3A and 3B, may be implemented in software code or instructionsthat are tangibly stored on a tangible computer readable medium. Uponloading and executing such software code or instructions by thecontroller and/or personal computing device, the controller and/orpersonal computing device may perform any of the functionality of thecontroller and/or personal computing device described herein, includingthe steps in 3A and 3B described herein.

It will be understood that the terms and expressions used herein havethe ordinary meaning as is accorded to such terms and expressions withrespect to their corresponding respective areas of inquiry and studyexcept where specific meanings have otherwise been set forth herein.Relational terms such as first and second and the like may be usedsolely to distinguish one entity or action from another withoutnecessarily requiring or implying any actual such relationship or orderbetween such entities or actions. The terms “comprises,” “comprising,”“includes,” “including,” or any other variation thereof, are intended tocover a non-exclusive inclusion, such that a process, method, article,or apparatus that comprises or includes a list of elements or steps doesnot include only those elements or steps but may include other elementsor steps not expressly listed or inherent to such process, method,article, or apparatus. An element preceded by “a” or “an” does not,without further constraints, preclude the existence of additionalidentical elements in the process, method, article, or apparatus thatcomprises the element.

Unless otherwise stated, any and all measurements, values, ratings,positions, magnitudes, sizes, and other specifications that are setforth in this specification, including in the claims that follow, areapproximate, not exact. Such amounts are intended to have a reasonablerange that is consistent with the functions to which they relate andwith what is customary in the art to which they pertain. For example,unless expressly stated otherwise, a parameter value or the like mayvary by as much as ±10% from the stated amount.

In addition, in the foregoing Detailed Description, it can be seen thatvarious features are grouped together in various examples for thepurpose of streamlining the disclosure. This method of disclosure is notto be interpreted as reflecting an intention that the claimed examplesrequire more features than are expressly recited in each claim. Rather,as the following claims reflect, the subject matter to be protected liesin less than all features of any single disclosed example. Thus, thefollowing claims are hereby incorporated into the Detailed Description,with each claim standing on its own as a separately claimed subjectmatter.

While the foregoing has described what are considered to be the bestmode and other examples, it is understood that various modifications maybe made therein and that the subject matter disclosed herein may beimplemented in various forms and examples, and that they may be appliedin numerous applications, only some of which have been described herein.It is intended by the following claims to claim any and allmodifications and variations that fall within the true scope of thepresent concepts.

What is claimed is:
 1. A system comprising: image capture eyewear,including: a support structure, and dual cameras connected to thesupport structure to capture stereoscopic images of a scene; a processorcoupled to the image capture eyewear; a memory accessible to theprocessor; and programming in the memory, wherein execution of theprogramming by the processor configures the system to perform functions,including functions to: capture, using the dual cameras, stereoscopicimages of the scene, the scene containing at least one object with knowndimensions; obtain a distance to the at least one object with knowndimensions based on a size of the at least one object with knowndimensions; identify an actual offset between the stereoscopic imagesfor the at least one object with known dimensions; determine a pluralityof calibration offsets as one of (1) a difference between the actualoffset and a previously determined offset for the at least one objectwith known dimensions determined with other image capture eyewear notexperiencing any flexure, or (2) an amount of flexure experienced by theimage capture eyewear; and store the calibration offsets in the memoryalong with flexure amounts corresponding to the calibration offsets. 2.The system of claim 1, wherein the support structure includes a frameand wherein execution of the programming by the processor furtherconfigures the system to perform functions, including functions to:determine an amount of flexure of the frame during use of the imagecapture eyewear; and generate a stereoscopic image using a calibrationoffset corresponding to the amount of flexure of the frame.
 3. Thesystem of claim 1, wherein the execution of the programming by theprocessor further configures the system to rectify the stereoscopicimages to remove distortion.
 4. The system of claim 1, wherein executionof the programming by the processor further configures the system toobtain the distance to the at least one object with known dimensions bydetermining at least one of a height or a width of the at least oneobject with known dimensions from bounding rectangles detected by a deepneural network.
 5. The system of claim 4, wherein the deep neuralnetwork is trained to directly estimate a distance to the at least oneobject with known dimensions.
 6. The system of claim 1, furthercomprising a laser measuring device incorporated into the supportstructure that provides a distance measurement to the at least oneobject with known dimensions.
 7. The system of claim 1, whereinexecution of the programming by the processor further configures thesystem to identify the actual offset between the stereoscopic images forthe at least one object with known dimensions by determining a number ofpixels between a position of a feature in a left image and a position ofthe feature in a right image in a horizontal direction as the actualoffset.
 8. The system of claim 1, further comprising a strain gauge inthe support structure, wherein execution of the programming by theprocessor further configures the system to determine the amount offlexure experienced by the image capture eyewear as an estimate based onpredefined calibration offset values associated with predefined levelsof strain measured by the strain gauge.
 9. A calibration method forimage capture eyewear, the method comprising the steps of: capturing,using dual cameras on a support structure of the image capture eyewear,stereoscopic images of a scene containing at least one object with knowndimensions; obtaining, using a processor coupled to the image captureeyewear, a distance to the at least one object with known dimensionsbased on a size of the at least one object with known dimensions;identifying, using the processor, an actual offset between thestereoscopic images for the at least one object with known dimensions;determining, using the processor, a plurality of calibration offsets asone of (1) a difference between the actual offset and a previouslydetermined offset for the at least one object with known dimensionsdetermined with other image capture eyewear not experiencing anyflexure, or (2) an amount of flexure experienced by the image captureeyewear; and storing the calibration offsets in a memory coupled to theprocessor along with flexure amounts corresponding to the calibrationoffsets.
 10. The method of claim 9, wherein the support structureincludes a frame, further comprising: determining an amount of flexureof the frame during use of the image capture eyewear; and generating astereoscopic image using a calibration offset corresponding to theamount of flexure of the frame.
 11. The method of claim 9, furthercomprising rectifying the stereoscopic images to remove distortion. 12.The method of claim 9, wherein obtaining the distance to the at leastone object with known dimensions includes determining at least one of aheight or a width of the at least one object with known dimensions frombounding rectangles detected by a deep neural network.
 13. The method ofclaim 12, further comprising training the deep neural network todirectly estimate a distance to the at least one object with knowndimensions.
 14. The method of claim 9, further comprising providing adistance measurement to the at least one object with known dimensionsusing a laser measuring device incorporated into the image captureeyewear.
 15. The method of claim 9, wherein identifying the actualoffset between the stereoscopic images for the at least one object withknown dimensions comprises determining a number of pixels between aposition of a feature in a left image and a position of the feature in aright image in a horizontal direction as the actual offset.
 16. Themethod of claim 9, further comprising determining the amount of flexureexperienced by the image capture eyewear as an estimate based onpredefined calibration offset values associated with predefined levelsof strain measured by a strain gauge.
 17. A non-transitory computerreadable medium comprising instructions which, when executed by one ormore processors, cause the one or more processors to calibrate imagecapture eyewear by performing operations comprising: capturingstereoscopic images of a scene containing at least one object with knowndimensions; obtaining a distance to the at least one object with knowndimensions based on a size of the at least one object with knowndimensions; identifying an actual offset between the stereoscopic imagesfor the at least one object with known dimensions; determining aplurality of calibration offsets as one of (1) a difference between theactual offset and a previously determined offset for the at least oneobject with known dimensions determined with other image capture eyewearnot experiencing any flexure, or (2) an amount of flexure experienced bythe image capture eyewear; and storing the calibration offsets in amemory along with flexure amounts corresponding to the calibrationoffsets.
 18. The medium of claim 17, wherein the instructions, whenexecuted by the one or more processors, further cause the one or moreprocessors to: determine an amount of flexure of a frame of the imagecapture eyewear during use of the image capture eyewear; and generate astereoscopic image using a calibration offset corresponding to theamount of flexure of the frame.
 19. The medium of claim 17, wherein theinstructions, when executed by the one or more processors, further causethe one or more processors to rectify the stereoscopic images to removedistortion.
 20. The medium of claim 17, wherein the instructions, whenexecuted by the one or more processors, further cause the one or moreprocessors to obtain the distance to the at least one object with knowndimensions by determining at least one of a height or a width of the atleast one object with known dimensions from bounding rectangles detectedby a deep neural network.